Recent developments in code compression techniques for embedded systems

•New Discovery yields a monster jump in processing embedded systems.•The compressed instructions are decompressed and implemented by the processor at the time of startup.•Several research techniques are surveyed including all the compressed and decompressed structures used in embedded systems.. Embe...

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Bibliographic Details
Published inMaterials today : proceedings Vol. 46; pp. 4128 - 4132
Main Authors Prasad, Dumpa, Rahul Reddy, P., Sreelatha, B., Jeevan Reddy, Koya, Jayabalan, Sudharsan, Kumar Panigrahy, Asisa
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.01.2021
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Summary:•New Discovery yields a monster jump in processing embedded systems.•The compressed instructions are decompressed and implemented by the processor at the time of startup.•Several research techniques are surveyed including all the compressed and decompressed structures used in embedded systems.. Embedded applications software code is increasingly growing in size. Whereas the entire code of all control panels in a car provided for roughly a few 100 K code lines a decade ago, a single control panel such as the engine control can now have up to 1million code lines. With these help of good approach, common scenarios are developed for other, even for mobiles, embedded systems like PDA’s, cell phones etc. However, increasing software size requires greater memory and can therefore raise the cost of an embedded system considerably. The starting of this pattern was already established in the early 1990 s. The compressed code is created by compressing the binary numbers using a code compression tool (at the time of design) is stored in the instruction memory of the embedded devices. The compressed instructions are decompressed and implemented by the processor at the time of startup. One of the serious challenges is that the tables will become wide in size and therefore decrease the benefits of compressing the code that could be accessed. Although the whole research in this area has mostly concentrated on improving greater code compression without specifically targeting the issue of wide look-up table sizes.
ISSN:2214-7853
2214-7853
DOI:10.1016/j.matpr.2021.02.643